1. Estimating a Population Proportion
Section 7.2
Estimating a Population Proportion

2. In Chapters 2 and 3 we used “descriptive statistics”.
Where Have We Been?
In Chapters 2 and 3 we used “descriptive statistics”.
We summarized data using tools such as graphs, mean, and standard deviation.

3. In Chapter 6 we began using “inferential statistics”.
Where Are We Going?
In Chapter 6 we began using “inferential statistics”.
We will be using sample data to make inferences about population parameters.

4. Goals – Ideas to Understand
How to find the best point estimate of the population proportion.
How to construct and interpret confidence intervals.
How to find the sample size necessary to estimate a population proportion.

5. Topic 1 – Point Estimate of a Population
Definition
Point Estimate: A single value (or point) used to approximate a population parameter.
Important Notes
If we want to estimate a population proportion with a single value, the best estimate is the sample proportion .
Unbiased (Section 6.7)
Most consistent

6. 70% of 1501 randomly selected adults in the U.S answered yes.
Topic 1- Example
In a Pew Research Center poll, respondents were asked “From what you’ve read and heard, is there solid evidence that the average temperature on earth has been increasing over the past few decades, or not?
70% of 1501 randomly selected adults in the U.S answered yes.
Find the best point estimate of the proportion of all adults in the U.S who believe in Global Warming.
The best estimate is 70%.

7. Topic 1 - Flaws
70% was our best point estimate of the population proportion p, but we have no idea of just how GOOD our best estimate is.
THINK: I could give you my best estimate for how awesome cats are. However, given my experience is based on only two cats, how good of a estimate is that for every cat?

8. TOPIC 2 – CONFIDENCE INTERVALS
Introducing …
TOPIC 2 – CONFIDENCE INTERVALS

9. Topic 2 – Confidence Intervals
Definition
Confidence Interval: A range (or interval) of values used to estimate the true value of a population parameter. Abbreviated CI.
Important Notes
A confidence level is expressed as the probability or area 1 –  , where  is the complement of the confidence level.
Most common choices are 90%, 95%, or 99%. This means (α = 10%), (α = 5%), (α = 1%)

10. Topic 2 – Interpreting Confidence Intervals
Correct
“We are 95% confident that the interval from to actually does contain the true value of the population proportion p.”
This means that if we were to select many different samples of size n and construct the corresponding confidence intervals, 95% of them would actually contain the value of the population proportion p.
Refers to the process.

11. Topic 2 – Interpreting Confidence Intervals
Incorrect
“There is a 95% chance that the true value of p will fall between and ”
“95% of sample proportions fall between and ”
“Mr. Llorens is more of a slick daddy than Ms. Pobuda.”
A confidence interval either contains p or it does not. That is why it is incorrect to say there is a 95% chance that p will fall between and

12. Topic 2 – Critical Values
A standard z score can be used to distinguish between sample statistics that are likely to occur and those that are unlikely to occur. Such a z score is called a critical value.
Definition
Critical Value: The number on the borderline separating sample statistics that are likely to occur from those that are unlikely to occur.

13. Topic 2 – Critical Clarification
The number z/2 is a critical value that is a z score with the property that it separates an area of /2 in the right tail of the standard normal distribution.

14. Topic 2 – Critical Example
Finding zα/2 (z*) for a 95% Confidence Level
Find /2
Subtract the result from 1.
Find the corresponding z score.

15. Topic 2 – Critical Practice
Confidence Level 
Critical Value, z/2
90%
0.10
1.645
95%
0.05
1.96
99%
0.01
2.575
Your turn. Complete the table.

16. Topic 2 – Margin of Error Definition
Margin of Error: When data from a simple random sample are used to estimate a population proportion p, the margin of error, denoted by E, is the maximum likely difference (with probability 1 – , such as 0.95) between the observed proportion and the true value of the population proportion p.
Important Notes
Mr. Llorens has a larger margin of error than Ms. Pobuda.

17. Topic 2 – Margin of Error Formula
Important Notes Margin of Error for Proportions

18. Topic 2 – Margin of Error Example
Assume that a sample is used to estimate a population proportion p. Find the margin of error, E, that corresponds to the given statistics and confidence level. Round the margin of error to three decimal places.
90% confidence, sample size is 500, of 20% are successes.
99% confidence, sample size is 300, of 25% are successes.

19. Topic 2 – Expressing A Margin of Error
3 different ways to write a confidence interval
Now express your answers from before as an interval.

20. Topic 3 – Point Estimate and E
Finding the Point Estimate and E from a Confidence Interval

21. CONSTRUCTING CONFIDENCE INTERVALS
Breathing Point
Learned about point estimate.
Defined confidence intervals.
Discovered how to find critical values and the margin of error.
Now the MAIN EVENT:
CONSTRUCTING CONFIDENCE INTERVALS
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22. Topic 2 – Putting it All Together
How To Guide: Constructing a Confidence Interval
Verify the sample is a simple, random sample and that the conditions for a binomial distribution are met.
Find the critical value zα/2
Evaluate the margin of error.
Find the values of the confidence interval limits.
Round the resulting confidence interval limits to three significant figures.

23. Constructing a Confidence Interval: Poll Results
Topic 2 – Example
Constructing a Confidence Interval: Poll Results
A poll of 1501 randomly selected U.S adults showed that 70% of the respondents believe in global warming.
Find the margin of error that corresponds to a 95% confidence interval.
Find the 95th confidence interval estimate of the population proportion p.
Based on the results, can we safely conclude that the majority of adults believe in global warming?

24. Topic 3 – Determining Sample Size
Objective
Determine how large the sample should be in order to estimate the population proportion p.
Requirements
The sample must be a simple random sample of independent subjects.
When an estimate of is known:
When an estimate of is unknown:

25. Topic 3 – Determining Sample Size
Important Note
Round-off Rule for Determining Sample Size
If the computed sample size n is not a whole number, round the value of n up to the next larger whole number.

26. Topic 3 – Determining Sample Size Example
How Many Adults Use the Internet?
An executive for E-Bay wants to determine the current percentage of U.S adults who now use the Internet. How many adults must be surveyed in order to be 95% confident that the sample percentage is in error by no more than three percentage points?
Use this result from a Pew Research Center poll: In 2006, 73% of U.S adults used the Internet.
Assume that we have no prior information suggesting a possible value of the proportion.

27. Topic 3 – Point Estimate and E
Finding the Point Estimate and E from a Confidence Interval

28. Topic 3 – Point Estimate and E Example
The article “High-Dose Nicotine Patch Therapy,” by Dale Hurt includes the statement: “Of the 71 subjects, 70% were abstinent from smoking at 8 weeks (95% confidence interval, 58% to 81%).” Use that statement to find the point estimate and margin of error E.

29. Practice Pg. 340-341 #5-8 (Finding Critical Values)
#9-10 (Expressing/Interpreting CI)
#17-20 (Finding Margin of Error)
#21-24 (Constructing Confidence Intervals)
#25-28 (Determining Sample Size)
#31, 32 (Application Problems)